Bibliographic record
Abstract
Sara Topelson de Grinberg, Arquitecta UNAM. Ha incursionado en el diseno, docencia, planeacion urbana, conservacion del patrimonio y publicaciones. De 1996 a 1999 fue la primera mujer Presidenta de la Union Internacional de Arquitectos (UIA). Academica Emerita de la Academia Nacional de Arquitectura. Ha sido merecedora de diversos reconocimientos, entre los que destacan el de Mujer del Ano Mexico 1996, Caballero de la Orden de Artes y Letras del Ministerio de Francia en 1998, Medalla al Merito Academico la Universidad Anahuac por 25 anos de excelencia en la docencia Miembro de Honor de: Instituto Americano de Arquitectos, Real Instituto de Arquitectos de Canada, Inglaterra, Australia, Japon Superior de los Colegios de Arquitectos de Espana, entre otros. De 2001 a 2003 fue Directora de Arquitectura y Conservacion del Patrimonio Artistico Inmueble del INBA, fomentando libros de temas relevantes de arquitectura, y 13 exposiciones en e Museo Nacional de Arquitectura. Subsecretaria de Desarrollo Urbano y Ordenacion del Territorio de la SEDESOL, de 2007 a 2012. Actualmente es Coordinadora de Proyectos en el despacho Grinberg y Topelson Arquitectos. Coordinadora del Centro de Investig Documentacion de la Casa “CIDOC”; publicando anualmente el estudio “Estado Actual de la Vivienda en Mexico” la doceava edicion en 2015.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.109 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".